The present invention relates to an apparatus for measuring the dynamic state of traffic, and more particularly an apparatus installed at a road to collect necessary traffic information such as the speed of vehicles, the number of vehicles passing, the types of cars (ordinary cars, large cars), etc.
Conventionally, an apparatus for measuring the dynamic state of traffic has been structured such that it can process both current picture data, which is a picked up image of vehicles on the road, and background data of the road. The conventional apparatus can also calculate the speed of vehicles, the number of vehicles passing, the types of vehicles (ordinary cars, large cars), etc. based on the processed data, and output the results.
In the conventional apparatus stated above, however, there has been a problem: since the apparatus is installed outdoor, it is necessary to update background data to follow the weather changes, etc. When the background data is updated by obtaining the difference in luminance between an original image and a background image and multiplying the difference by a predetermined ratio, the background data can be brought into disorder because the updating is carried out even when the road is unseen due to traffic congestion or other reasons.
Further, according to the above-described conventional apparatus, there has also been a problem in that shadows of vehicles on the adjacent traffic lanes are misjudged as being vehicles when the picture is processed, or the shadow of the front portion of a vehicle is misjudged as being the front edge portion of the vehicle, thus causing an erroneous detection.
Further, there has also been a problem in that, when the luminance of the vehicle is decreased at dusk, it is hard to detect vehicles, not to mention those having a dark color with little difference of luminance from that of the road surface. Vehicles having bright color, with large differences of luminance are also hard to detect. Conventionally, it is impossible to eliminate all the unnecessary images of shadows even if image processing using only plus components is carried out. Here, the plus components are non-zero and non-negative components in the result of both the difference of background and the difference between frames, the former being the difference at each of the picture elements between the original image and the background image, while the latter is the difference at each of the picture elements between images taken at a time interval .DELTA.t. Therefore, an end edge portion of the shadow of vehicle may be detected as being a vehicle due to the difference between frames, resulting in a misjudgement and erroneous detection if the vehicle is running at high-speed or if it is a large car. Here, the difference between frames is the difference at each of the picture elements between original images taken at the time interval .DELTA.t.
Since image processings using only plus components are carried out, it is not possible to completely extract vehicle images from the normal processed screen pictures when there is small difference of luminance between black cars and the road surface on the video screen so that black cars may not be detected even in the daytime.